Collection in High Court Libraries of India: A Survey (2005 to 2009)

With the ever increasing cost of the publications, the collection development in High court libraries of India has been markedly effected. This paper tries to find out that  due to changing environment, has  the collection  increased ,decreased or remain stagnant 

Learning Optimal Control of Synchronization in Networks of Coupled Oscillators using Genetic Programming-based Symbolic Regression

Networks of coupled dynamical systems provide a powerful way to model systems with enormously complex dynamics, such as the human brain. Control of synchronization in such networked systems has far reaching applications in many domains, including engineering and medicine. In this paper, we formulate the synchronization control in dynamical systems as an optimization problem and present a multi-objective genetic programming-based approach to infer optimal control functions that drive the system from a synchronized to a non-synchronized state and vice-versa. The genetic programming-based controller allows learning optimal control functions in an interpretable symbolic form. The effectiveness of the proposed approach is demonstrated in controlling synchronization in coupled oscillator systems linked in networks of increasing order complexity, ranging from a simple coupled oscillator system to a hierarchical network of coupled oscillators. The results show that the proposed method can learn highly-effective and interpretable control functions for such systems.Comment: Submitted to nonlinear dynamic

Prevalence of different tick species on livestock and associated equines and canine from different agro-ecological zones of Pakistan

Ticks are ectoparasites that act as vectors for transmission of various pathogens to wild and domesticated animals and pose a serious threat to human health. Because of the hot and humid conditions in different agro-ecological zones of Pakistan, ticks are abundant and parasitize a variety of animals. The aim of this study was to identify different tick species and distribution on different hosts especially livestock, such as sheep, goat, cattle, buffalo, and camel, and livestock associated canines and equines, such as horse, donkey, and dog, across different agro-ecological zones of Pakistan. The ticks samples were collected and morphologically identified at genus and species level using morphological keys under stereomicroscope. A total of 2,846 animals were examined for the tick infestation, and 408 animals were tick-infested. Eleven tick species belonging to 4 genera were identified: Hyalomma anatolicum, Hyalomma scupense, Hyalomma dromedarii, Hyalomma isaaci, Rhipicephalus microplus, Rhipicephalus haemaphysaloides, Rhipicephalus turanicus, Haemaphysalis cornupunctata, Haemaphysalis montgomeryi, Haemaphysalis bispinosa, and Ixodes kashmiricus. The overall tick prevalence was 14.3%; host-wise infestation rate was 12.2% in sheep; 12.6%, goat; 11.7%, buffalo; 11.7%, cattle; 19.6%, camel; 27.4%, donkey; 23.5%, horse; and 24.3%, dog. Tick infestation of different animals differed on the basis of the zones. Camels showed the highest tick infestation rate in zones 1 and 2 (21.4 and 26.7%, respectively), whereas donkeys showed the highest infestation rate in zones 3, 4, 6, and 7 (25, 39.3, 3.3, and 21.4%, respectively). The infestation rates of Hyalomma and Rhipicephalus were the highest in zone 2 (71.4 and 52.9%, respectively). The infestation rate of Hyalomma was the highest (47.4%) in sheep; Haemaphysalis (46.9%), goat; Rhipicephalus (69.7%), buffalo; Rhipicephalus (62.3%), cattle; Hyalomma (70%), camel; Ixodes (60.9%), donkey; Ixodes (75%), horse; and Rhipicephalus (61.1%), dog. This study showed the diversity and infestation rate of different ticks with respect to their hosts and agro-ecological zones of Pakistan. High tick burdens and infestation rates are responsible for the spread of different tick-borne infections, resulting in loss of animal productivity and posing a threat to animal and human health. Understanding different tick species and their distribution across different zones will be helpful for developing efficient control strategies against different tick born infections

Predictors of Death in the Liver Transplantation Adult Candidates: An Artificial Neural Networks and Support Vector Machine Hybrid-Based Cohort Study

Background: Model for end-stage liver disease (MELD) is currently used for liver transplantation (LT) allocation, however, it is not a sufficient criterion. Objective: This current study aims to perform a hybrid neural network analysis of different data, make a decision tree and finally design a decision support system for improving LT prioritization.Material and Methods: In this cohort follow-up-based study, baseline characteristics of 1947 adult patients, who were candidates for LT in Shiraz Organ Transplant Center, Iran, were assessed and followed for two years and those who died before LT due to the end-stage liver disease were considered as dead cases, while others considered as alive cases. A well-organized checklist was filled for each patient. Analysis of the data was performed using artificial neural networks (ANN) and support vector machines (SVM). Finally, a decision tree was illustrated and a user friendly decision support system was designed to assist physicians in LT prioritization. Results: Between all MELD types, MELD-Na was a stronger determinant of LT candidates’ survival. Both ANN and SVM showed that besides MELD-Na, age and ALP (alkaline phosphatase) are the most important factors, resulting in death in LT candidates. It was cleared that MELD-Na <23, age <53 and ALP <257 IU/L were the best predictors of survival in LT candidates. An applicable decision support system was designed in this study using the above three factors.  Conclusion: Therefore, Meld-Na, age and ALP should be used for LT allocation. The presented decision support system in this study will be helpful in LT prioritization by LT allocators

The role of early stopping and population size in xcs for intrusion detection

Evolutionary Learning Classifier Systems (LCSs) are rule based systems that have been used effectively in concept learning. XCS is a prominent LCS that uses genetic algorithms and reinforcement learning techniques. In traditional machine learning, early stopping have been investigated extensively to an extent that it is now a default mechanism in many systems. There has been a belief that EC methods are more resilient to overfitting. Therefore, this topic is under-investigated in the evolutionary computation literature and has not been investigated in LCS. In this paper, we show that it is necessary to stop evolution in LCS using a stopping criteria other than a maximum number of generations and that evolution may suffer from overfitting similar to other ML methods. I

Measurement of Job Wellbeing Behaviors by Perceived Narcissistic Supervision and Workplace Bullying: The Mediating Role of Emotional Exhaustions: Kamran Khan, Tahira Nazir, Khuram Shafi

The objective of the study is to examine the job wellbeing behaviors by perceived narcissistic supervision and workplace bullying. It also determines the mediating role of emotional exhaustions among the study variables. The data of 395 of employees was collected from banking and telecom sectors organizations located in Rawalpindi and Islamabad. The data was collected in English language administered scales and relationships among variables were examined by using process macro of Preacher and Hayes 2003. Results of the study revealed a significant negative direct association among perceived narcissistic supervision, workplace bullying, and wellbeing behaviors. Further indirect relation between variables significantly was tested by the mediating role of emotional exhaustions among the study variables. Drawing upon the Conservation of resources theory (COR), the present study has contributed to the literature of adverse working conditions with their relationship of job wellbeing behaviors. The obtained results identified the need for the organization to set the wellbeing behaviors and implement policies with response to workplace bullying and perceived narcissistic supervision. Limitations and future directions are provided for further studies in these areas